Table 3.

Model performance for external validation dataset (product of sensitivity and specificity is maximized).

Models	AUC	Threshold	Sensitivity	Specificity
THEATER BBN	0.68 [0.58,0.78]	0.53 [0.49,0.58]	0.66 [0.43,0.88]	0.66 [0.45,0.88]
THEATER TRMS	0.72 [0.63,0.81]	1	0.74 [0.64,0.85]	0.69 [0.55,0.82]
THEATER BBN + TRMS	0.71 [0.63,0.80]	0.89 [0.58,1.0]	0.76 [0.67,0.86]	0.69 [0.55,0.82]
THEATER BBN + TRMNS	0.77 [0.69,0.84]	0.42 [0.12,0.49]	0.70 [0.58,0.82]	0.83 [0.70,0.94]
MEDCEN BBN	0.67 [0.57,0.78]	0.51 [0.48,0.53]	0.64 [0.47,0.85]	0.69 [0.49,0.86]
MEDCEN TRMS	0.71 [0.63,0.81]	1	0.74 [0.63,0.87]	0.68 [0.53,0.80]
MEDCEN BBN + TRMS	0.70 [0.61,0.80]	0.90 [0.53,1]	0.76 [0.65,0.87]	0.67 [0.53,0.807]
MEDCEN BBN + TRMNS	0.76 [0.68,0.85]	0.42 [0.11,0.50]	0.70 [0.58,0.82]	0.82 [0.70,0.92]

BBN = Bayesian Belief Network (produces a probability for having IFI)

TRMS = Two-rule Model Satisified (assigns 1 if satisfied, and 0 otherwise)

BBN + TRMS = Bayesian Belief Network plus Two-rule Model Satisfied (assigns 1 if TRM is satisfied, otherwise BBN produces a probability for having IFI)

BBN + TRMNS = Bayesian Belief Network plus Two-rule Model Not Satisfied (assigns 0 if TRM is not satisfied, otherwise BBN produces a probability for having IFI)